Cleavage Factor Binding Densities
Mervin M Fansler
10 April 2023
Purpose
Visualizes cleavage factor binding densities relative to the cleavage sites in the human UTRome annotation.
Initialization
Libraries
library(plyranges)
library(BiocParallel)
library(tidyverse)
library(magrittr)
library(cowplot)Parameters
EPSILON = 20
TPM = 5
WIN_SIZE = 1000
MIN_SCORE = 0 ## POSTAR score [0-1]
N_CTS_LOW = 10
N_CTS_HIGH = 80
DIR_POSTAR = "../crispr-utr/data/postar"
FILE_UTROME = sprintf("data/granges/utrome_gr_txs.e%d.t%d.gc39.pas3.f0.9999.w500.Rds",
EPSILON, TPM)
FILE_BED_UNLIKELY = sprintf("data/bed/cleavage-sites/utrome.unlikely.e%d.t%d.gc39.pas3.f0.9999.bed.gz",
EPSILON, TPM)
FILE_BED = sprintf("data/bed/celltypes/celltypes.e%d.t%d.bed.gz", EPSILON, TPM)Functions
## intersects GRanges, returning midpoints of gr_factor intervals
## relative to the gr_txs intervals
get_centered_overlaps <- function (gr_factor, gr_txs, name) {
grs <- findOverlapPairs(gr_factor, gr_txs)
sign <- strand(grs@second) == '+'
start <- ifelse(sign,
start(grs@first) - start(grs@second) - width(grs@second)/2,
start(grs@second) - end(grs@first) + width(grs@second)/2)
end <- ifelse(sign,
end(grs@first) - start(grs@second) - width(grs@second)/2,
start(grs@second) - start(grs@first) + width(grs@second)/2)
IRanges(start=start, end=end, names=Rle(name, length(start)))
}
## plot density from genomic ranges object
plot_gr_density <- function (gr, RADIUS=300, palette="Set3", title="UTRome") {
n_cfs <- gr %>% names %>% unique %>% length
cols <- RColorBrewer::brewer.pal(n=n_cfs+2, name=palette)[2:(n_cfs+1)]
as.data.frame(gr) %>%
mutate(midpoint=(end+start)/2) %>%
rename(cleavage_factor=names) %>%
ggplot(aes(x=midpoint, color=cleavage_factor)) +
stat_density(aes(y=..scaled..), geom='line', position='identity',
size=1.5, alpha=0.9) +
geom_hline(yintercept=0) +
geom_vline(xintercept=0, linetype='dashed', color='black') +
coord_cartesian(xlim=c(-RADIUS, RADIUS)) +
scale_x_continuous(breaks=seq(-RADIUS, RADIUS, 100),
limits=c(-RADIUS - 100, RADIUS+100)) +
scale_color_manual(values=cols) +
labs(x=sprintf("Distance from Cleavage Site (%s)", title),
y="Relative Density", color="Factor") +
guides(color=guide_legend(override.aes=list(alpha=1, size=3))) +
theme_minimal_vgrid()
}Load Data
Human UTRome Transcripts
## Load all transcripts
gr_txs <- readRDS(FILE_UTROME)
## focus on cleavage sites
gr_cleavage <- gr_txs %>%
anchor_3p %>%
mutate(width=WIN_SIZE) %>%
shift_downstream(WIN_SIZE/2)Cleavage Sites by Cell Type
gr_sites <- read_bed(FILE_BED) %>%
`seqlevelsStyle<-`("UCSC") %>%
keepStandardChromosomes(pruning.mode="coarse") %>%
anchor_center() %>%
mutate(width=20)Cleavage Sites Marked as Internal Priming
gr_ip <- read_bed(FILE_BED_UNLIKELY) %>%
anchor_3p %>%
mutate(width=WIN_SIZE) %>%
shift_downstream(WIN_SIZE/2)Annotation with Number of Supporting Cell Types
gr_cleavage %<>%
mutate(n_celltypes=count_overlaps_directed(gr_cleavage, gr_sites))Subgroups
gr_single <- filter(gr_cleavage, utr_type == "single")
gr_ipa <- filter(gr_cleavage, is_ipa)
gr_multi_tandem <- filter(gr_cleavage, utr_type == 'multi', !is_ipa)
gr_gencode <- filter(gr_cleavage, !is_novel)
gr_novel <- filter(gr_cleavage, is_novel)
gr_proximal_gc <- filter(gr_cleavage, utr_type == 'multi', is_proximal, !is_novel)
gr_distal_gc <- filter(gr_cleavage, utr_type == 'multi', is_distal, !is_novel)
gr_proximal_novel <- filter(gr_cleavage, utr_type == 'multi', is_proximal, is_novel)
gr_distal_novel <- filter(gr_cleavage, utr_type == 'multi', is_distal, is_novel)
gr_ctnone_gc <- filter(gr_cleavage, !is_novel, n_celltypes == 0)
gr_ctlow_gc <- filter(gr_cleavage, !is_novel, n_celltypes > 0, n_celltypes < N_CTS_LOW)
gr_ctmid_gc <- filter(gr_cleavage, !is_novel, n_celltypes >= N_CTS_LOW, n_celltypes < N_CTS_HIGH)
gr_cthigh_gc <- filter(gr_cleavage, !is_novel, n_celltypes >= N_CTS_HIGH)
gr_ctlow_novel <- filter(gr_cleavage, is_novel, n_celltypes < N_CTS_LOW)
gr_ctmid_novel <- filter(gr_cleavage, is_novel, n_celltypes >= N_CTS_LOW, n_celltypes < N_CTS_HIGH)
gr_cthigh_novel <- filter(gr_cleavage, is_novel, n_celltypes >= N_CTS_HIGH)Helper Methods
## capture Hg38 SeqInfo
si_hg38 <- seqinfo(gr_txs)
## loads POSTAR data
load_postar_sites <- function (rbp, si=si_hg38, min_score=MIN_SCORE) {
file <- sprintf("%s/%s.binding.sites", DIR_POSTAR, rbp)
gr <- read_tsv(file, col_types='cii__cc___d___________',
col_names=c('seqnames', 'start', 'end', 'strand', 'gene_symbol', 'score')) %>%
as_granges %>%
filter(score >= min_score) %>%
keepStandardChromosomes(species="Homo_sapiens", pruning.mode='coarse')
seqlevels(gr) <- seqlevels(si)
seqinfo(gr) <- si
gr
}POSTAR Data
gr_nudt21 <- load_postar_sites("NUDT21")
gr_cpsf6 <- load_postar_sites("CPSF6")
gr_cpsf1 <- load_postar_sites("CPSF1")
gr_cpsf2 <- load_postar_sites("CPSF2")
gr_cpsf3 <- load_postar_sites("CPSF3")
gr_cpsf4 <- load_postar_sites("CPSF4")
gr_wdr33 <- load_postar_sites("WDR33")
gr_fip1l1 <- load_postar_sites("FIP1L1")
gr_cstf2 <- load_postar_sites("CSTF2")
gr_cstf2t <- load_postar_sites("CSTF2T")Plots
All Sites
gr_subset <- gr_cleavage
c(get_centered_overlaps(gr_nudt21, gr_subset, "NUDT21"),
get_centered_overlaps(gr_cpsf6, gr_subset, "CPSF6")) %>%
plot_gr_density(palette="Blues")
c(get_centered_overlaps(gr_cpsf1, gr_subset, "CPSF1"),
get_centered_overlaps(gr_cpsf2, gr_subset, "CPSF2"),
get_centered_overlaps(gr_cpsf3, gr_subset, "CPSF3"),
get_centered_overlaps(gr_cpsf4, gr_subset, "CPSF4"),
get_centered_overlaps(gr_wdr33, gr_subset, "WDR33"),
get_centered_overlaps(gr_fip1l1, gr_subset, "FIP1L1")) %>%
plot_gr_density(palette="Greens")
c(get_centered_overlaps(gr_cstf2, gr_subset, "CSTF2"),
get_centered_overlaps(gr_cstf2t, gr_subset, "CSTF2Ï„")) %>%
plot_gr_density(palette="Reds")
Single UTR Genes
gr_subset <- gr_single
plot_title <- "Single-UTR Genes"
c(get_centered_overlaps(gr_nudt21, gr_subset, "NUDT21"),
get_centered_overlaps(gr_cpsf6, gr_subset, "CPSF6")) %>%
plot_gr_density(palette="Blues", title=plot_title)
c(get_centered_overlaps(gr_cpsf1, gr_subset, "CPSF1"),
get_centered_overlaps(gr_cpsf2, gr_subset, "CPSF2"),
get_centered_overlaps(gr_cpsf3, gr_subset, "CPSF3"),
get_centered_overlaps(gr_cpsf4, gr_subset, "CPSF4"),
get_centered_overlaps(gr_wdr33, gr_subset, "WDR33"),
get_centered_overlaps(gr_fip1l1, gr_subset, "FIP1L1")) %>%
plot_gr_density(palette="Greens", title=plot_title)
c(get_centered_overlaps(gr_cstf2, gr_subset, "CSTF2"),
get_centered_overlaps(gr_cstf2t, gr_subset, "CSTF2Ï„")) %>%
plot_gr_density(palette="Reds", title=plot_title)
Intronic Cleavage Sites
gr_subset <- gr_ipa
plot_title <- "Intronic Sites"
c(get_centered_overlaps(gr_nudt21, gr_subset, "NUDT21"),
get_centered_overlaps(gr_cpsf6, gr_subset, "CPSF6")) %>%
plot_gr_density(palette="Blues", title=plot_title)
c(get_centered_overlaps(gr_cpsf1, gr_subset, "CPSF1"),
get_centered_overlaps(gr_cpsf2, gr_subset, "CPSF2"),
get_centered_overlaps(gr_cpsf3, gr_subset, "CPSF3"),
get_centered_overlaps(gr_cpsf4, gr_subset, "CPSF4"),
get_centered_overlaps(gr_wdr33, gr_subset, "WDR33"),
get_centered_overlaps(gr_fip1l1, gr_subset, "FIP1L1")) %>%
plot_gr_density(palette="Greens", title=plot_title)
c(get_centered_overlaps(gr_cstf2, gr_subset, "CSTF2"),
get_centered_overlaps(gr_cstf2t, gr_subset, "CSTF2Ï„")) %>%
plot_gr_density(palette="Reds", title=plot_title)
Tandem Multi-UTR Gene Sites
gr_subset <- gr_multi_tandem
plot_title <- "Tandem Sites"
c(get_centered_overlaps(gr_nudt21, gr_subset, "NUDT21"),
get_centered_overlaps(gr_cpsf6, gr_subset, "CPSF6")) %>%
plot_gr_density(palette="Blues", title=plot_title)
c(get_centered_overlaps(gr_cpsf1, gr_subset, "CPSF1"),
get_centered_overlaps(gr_cpsf2, gr_subset, "CPSF2"),
get_centered_overlaps(gr_cpsf3, gr_subset, "CPSF3"),
get_centered_overlaps(gr_cpsf4, gr_subset, "CPSF4"),
get_centered_overlaps(gr_wdr33, gr_subset, "WDR33"),
get_centered_overlaps(gr_fip1l1, gr_subset, "FIP1L1")) %>%
plot_gr_density(palette="Greens", title=plot_title)
c(get_centered_overlaps(gr_cstf2, gr_subset, "CSTF2"),
get_centered_overlaps(gr_cstf2t, gr_subset, "CSTF2Ï„")) %>%
plot_gr_density(palette="Reds", title=plot_title)
GENCODE
All Cleavage Sites
gr_subset <- gr_gencode
plot_title <- "GENCODE"
c(get_centered_overlaps(gr_nudt21, gr_subset, "NUDT21"),
get_centered_overlaps(gr_cpsf6, gr_subset, "CPSF6")) %>%
plot_gr_density(palette="Blues", title=plot_title)
c(get_centered_overlaps(gr_cpsf1, gr_subset, "CPSF1"),
get_centered_overlaps(gr_cpsf2, gr_subset, "CPSF2"),
get_centered_overlaps(gr_cpsf3, gr_subset, "CPSF3"),
get_centered_overlaps(gr_cpsf4, gr_subset, "CPSF4"),
get_centered_overlaps(gr_wdr33, gr_subset, "WDR33"),
get_centered_overlaps(gr_fip1l1, gr_subset, "FIP1L1")) %>%
plot_gr_density(palette="Greens", title=plot_title)
c(get_centered_overlaps(gr_cstf2, gr_subset, "CSTF2"),
get_centered_overlaps(gr_cstf2t, gr_subset, "CSTF2Ï„")) %>%
plot_gr_density(palette="Reds", title=plot_title)
Proximal Cleavage Sites
gr_subset <- gr_proximal_gc
plot_title <- "Proximal Sites - GENCODE"
c(get_centered_overlaps(gr_nudt21, gr_subset, "NUDT21"),
get_centered_overlaps(gr_cpsf6, gr_subset, "CPSF6")) %>%
plot_gr_density(palette="Blues", title=plot_title)
c(get_centered_overlaps(gr_cpsf1, gr_subset, "CPSF1"),
get_centered_overlaps(gr_cpsf2, gr_subset, "CPSF2"),
get_centered_overlaps(gr_cpsf3, gr_subset, "CPSF3"),
get_centered_overlaps(gr_cpsf4, gr_subset, "CPSF4"),
get_centered_overlaps(gr_wdr33, gr_subset, "WDR33"),
get_centered_overlaps(gr_fip1l1, gr_subset, "FIP1L1")) %>%
plot_gr_density(palette="Greens", title=plot_title)
c(get_centered_overlaps(gr_cstf2, gr_subset, "CSTF2"),
get_centered_overlaps(gr_cstf2t, gr_subset, "CSTF2Ï„")) %>%
plot_gr_density(palette="Reds", title=plot_title)
Distal Cleavage Sites
gr_subset <- gr_distal_gc
plot_title <- "Distal Sites - GENCODE"
c(get_centered_overlaps(gr_nudt21, gr_subset, "NUDT21"),
get_centered_overlaps(gr_cpsf6, gr_subset, "CPSF6")) %>%
plot_gr_density(palette="Blues", title=plot_title)
c(get_centered_overlaps(gr_cpsf1, gr_subset, "CPSF1"),
get_centered_overlaps(gr_cpsf2, gr_subset, "CPSF2"),
get_centered_overlaps(gr_cpsf3, gr_subset, "CPSF3"),
get_centered_overlaps(gr_cpsf4, gr_subset, "CPSF4"),
get_centered_overlaps(gr_wdr33, gr_subset, "WDR33"),
get_centered_overlaps(gr_fip1l1, gr_subset, "FIP1L1")) %>%
plot_gr_density(palette="Greens", title=plot_title)
c(get_centered_overlaps(gr_cstf2, gr_subset, "CSTF2"),
get_centered_overlaps(gr_cstf2t, gr_subset, "CSTF2Ï„")) %>%
plot_gr_density(palette="Reds", title=plot_title)
Cell Types High
gr_subset <- gr_cthigh_gc
plot_title <- "Cell Types High - GENCODE"
c(get_centered_overlaps(gr_nudt21, gr_subset, "NUDT21"),
get_centered_overlaps(gr_cpsf6, gr_subset, "CPSF6")) %>%
plot_gr_density(palette="Blues", title=plot_title)
c(get_centered_overlaps(gr_cpsf1, gr_subset, "CPSF1"),
get_centered_overlaps(gr_cpsf2, gr_subset, "CPSF2"),
get_centered_overlaps(gr_cpsf3, gr_subset, "CPSF3"),
get_centered_overlaps(gr_cpsf4, gr_subset, "CPSF4"),
get_centered_overlaps(gr_wdr33, gr_subset, "WDR33"),
get_centered_overlaps(gr_fip1l1, gr_subset, "FIP1L1")) %>%
plot_gr_density(palette="Greens", title=plot_title)
c(get_centered_overlaps(gr_cstf2, gr_subset, "CSTF2"),
get_centered_overlaps(gr_cstf2t, gr_subset, "CSTF2Ï„")) %>%
plot_gr_density(palette="Reds", title=plot_title)
Cell Types Midrange
gr_subset <- gr_ctmid_gc
plot_title <- "Cell Types Midrange - GENCODE"
c(get_centered_overlaps(gr_nudt21, gr_subset, "NUDT21"),
get_centered_overlaps(gr_cpsf6, gr_subset, "CPSF6")) %>%
plot_gr_density(palette="Blues", title=plot_title)
c(get_centered_overlaps(gr_cpsf1, gr_subset, "CPSF1"),
get_centered_overlaps(gr_cpsf2, gr_subset, "CPSF2"),
get_centered_overlaps(gr_cpsf3, gr_subset, "CPSF3"),
get_centered_overlaps(gr_cpsf4, gr_subset, "CPSF4"),
get_centered_overlaps(gr_wdr33, gr_subset, "WDR33"),
get_centered_overlaps(gr_fip1l1, gr_subset, "FIP1L1")) %>%
plot_gr_density(palette="Greens", title=plot_title)
c(get_centered_overlaps(gr_cstf2, gr_subset, "CSTF2"),
get_centered_overlaps(gr_cstf2t, gr_subset, "CSTF2Ï„")) %>%
plot_gr_density(palette="Reds", title=plot_title)
Cell Types Low
gr_subset <- gr_ctlow_gc
plot_title <- "Cell Types Low - GENCODE"
c(get_centered_overlaps(gr_nudt21, gr_subset, "NUDT21"),
get_centered_overlaps(gr_cpsf6, gr_subset, "CPSF6")) %>%
plot_gr_density(palette="Blues", title=plot_title)
c(get_centered_overlaps(gr_cpsf1, gr_subset, "CPSF1"),
get_centered_overlaps(gr_cpsf2, gr_subset, "CPSF2"),
get_centered_overlaps(gr_cpsf3, gr_subset, "CPSF3"),
get_centered_overlaps(gr_cpsf4, gr_subset, "CPSF4"),
get_centered_overlaps(gr_wdr33, gr_subset, "WDR33"),
get_centered_overlaps(gr_fip1l1, gr_subset, "FIP1L1")) %>%
plot_gr_density(palette="Greens", title=plot_title)
c(get_centered_overlaps(gr_cstf2, gr_subset, "CSTF2"),
get_centered_overlaps(gr_cstf2t, gr_subset, "CSTF2Ï„")) %>%
plot_gr_density(palette="Reds", title=plot_title)
No Cell Types Supporting
gr_subset <- gr_ctnone_gc
plot_title <- "No Cell Types Supporting - GENCODE"
c(get_centered_overlaps(gr_nudt21, gr_subset, "NUDT21"),
get_centered_overlaps(gr_cpsf6, gr_subset, "CPSF6")) %>%
plot_gr_density(palette="Blues", title=plot_title)
c(get_centered_overlaps(gr_cpsf1, gr_subset, "CPSF1"),
get_centered_overlaps(gr_cpsf2, gr_subset, "CPSF2"),
get_centered_overlaps(gr_cpsf3, gr_subset, "CPSF3"),
get_centered_overlaps(gr_cpsf4, gr_subset, "CPSF4"),
get_centered_overlaps(gr_wdr33, gr_subset, "WDR33"),
get_centered_overlaps(gr_fip1l1, gr_subset, "FIP1L1")) %>%
plot_gr_density(palette="Greens", title=plot_title)
c(get_centered_overlaps(gr_cstf2, gr_subset, "CSTF2"),
get_centered_overlaps(gr_cstf2t, gr_subset, "CSTF2Ï„")) %>%
plot_gr_density(palette="Reds", title=plot_title)
Novel
All Cleavage Sites
gr_subset <- gr_novel
plot_title <- "Novel Sites"
c(get_centered_overlaps(gr_nudt21, gr_subset, "NUDT21"),
get_centered_overlaps(gr_cpsf6, gr_subset, "CPSF6")) %>%
plot_gr_density(palette="Blues", title=plot_title)
c(get_centered_overlaps(gr_cpsf1, gr_subset, "CPSF1"),
get_centered_overlaps(gr_cpsf2, gr_subset, "CPSF2"),
get_centered_overlaps(gr_cpsf3, gr_subset, "CPSF3"),
get_centered_overlaps(gr_cpsf4, gr_subset, "CPSF4"),
get_centered_overlaps(gr_wdr33, gr_subset, "WDR33"),
get_centered_overlaps(gr_fip1l1, gr_subset, "FIP1L1")) %>%
plot_gr_density(palette="Greens", title=plot_title)
c(get_centered_overlaps(gr_cstf2, gr_subset, "CSTF2"),
get_centered_overlaps(gr_cstf2t, gr_subset, "CSTF2Ï„")) %>%
plot_gr_density(palette="Reds", title=plot_title)
Proximal Cleavage Sites
gr_subset <- gr_proximal_novel
plot_title <- "Proximal Sites - novel"
c(get_centered_overlaps(gr_nudt21, gr_subset, "NUDT21"),
get_centered_overlaps(gr_cpsf6, gr_subset, "CPSF6")) %>%
plot_gr_density(palette="Blues", title=plot_title)
c(get_centered_overlaps(gr_cpsf1, gr_subset, "CPSF1"),
get_centered_overlaps(gr_cpsf2, gr_subset, "CPSF2"),
get_centered_overlaps(gr_cpsf3, gr_subset, "CPSF3"),
get_centered_overlaps(gr_cpsf4, gr_subset, "CPSF4"),
get_centered_overlaps(gr_wdr33, gr_subset, "WDR33"),
get_centered_overlaps(gr_fip1l1, gr_subset, "FIP1L1")) %>%
plot_gr_density(palette="Greens", title=plot_title)
c(get_centered_overlaps(gr_cstf2, gr_subset, "CSTF2"),
get_centered_overlaps(gr_cstf2t, gr_subset, "CSTF2Ï„")) %>%
plot_gr_density(palette="Reds", title=plot_title)
Distal Cleavage Sites
gr_subset <- gr_distal_novel
plot_title <- "Distal Sites - novel"
c(get_centered_overlaps(gr_nudt21, gr_subset, "NUDT21"),
get_centered_overlaps(gr_cpsf6, gr_subset, "CPSF6")) %>%
plot_gr_density(palette="Blues", title=plot_title)
c(get_centered_overlaps(gr_cpsf1, gr_subset, "CPSF1"),
get_centered_overlaps(gr_cpsf2, gr_subset, "CPSF2"),
get_centered_overlaps(gr_cpsf3, gr_subset, "CPSF3"),
get_centered_overlaps(gr_cpsf4, gr_subset, "CPSF4"),
get_centered_overlaps(gr_wdr33, gr_subset, "WDR33"),
get_centered_overlaps(gr_fip1l1, gr_subset, "FIP1L1")) %>%
plot_gr_density(palette="Greens", title=plot_title)
c(get_centered_overlaps(gr_cstf2, gr_subset, "CSTF2"),
get_centered_overlaps(gr_cstf2t, gr_subset, "CSTF2Ï„")) %>%
plot_gr_density(palette="Reds", title=plot_title)
Cell Types High
gr_subset <- gr_cthigh_novel
plot_title <- "Cell Types High - novel"
c(get_centered_overlaps(gr_nudt21, gr_subset, "NUDT21"),
get_centered_overlaps(gr_cpsf6, gr_subset, "CPSF6")) %>%
plot_gr_density(palette="Blues", title=plot_title)
c(get_centered_overlaps(gr_cpsf1, gr_subset, "CPSF1"),
get_centered_overlaps(gr_cpsf2, gr_subset, "CPSF2"),
get_centered_overlaps(gr_cpsf3, gr_subset, "CPSF3"),
get_centered_overlaps(gr_cpsf4, gr_subset, "CPSF4"),
get_centered_overlaps(gr_wdr33, gr_subset, "WDR33"),
get_centered_overlaps(gr_fip1l1, gr_subset, "FIP1L1")) %>%
plot_gr_density(palette="Greens", title=plot_title)
c(get_centered_overlaps(gr_cstf2, gr_subset, "CSTF2"),
get_centered_overlaps(gr_cstf2t, gr_subset, "CSTF2Ï„")) %>%
plot_gr_density(palette="Reds", title=plot_title)
Cell Types Midrange
gr_subset <- gr_ctmid_novel
plot_title <- "Cell Types Midrange - novel"
c(get_centered_overlaps(gr_nudt21, gr_subset, "NUDT21"),
get_centered_overlaps(gr_cpsf6, gr_subset, "CPSF6")) %>%
plot_gr_density(palette="Blues", title=plot_title)
c(get_centered_overlaps(gr_cpsf1, gr_subset, "CPSF1"),
get_centered_overlaps(gr_cpsf2, gr_subset, "CPSF2"),
get_centered_overlaps(gr_cpsf3, gr_subset, "CPSF3"),
get_centered_overlaps(gr_cpsf4, gr_subset, "CPSF4"),
get_centered_overlaps(gr_wdr33, gr_subset, "WDR33"),
get_centered_overlaps(gr_fip1l1, gr_subset, "FIP1L1")) %>%
plot_gr_density(palette="Greens", title=plot_title)
c(get_centered_overlaps(gr_cstf2, gr_subset, "CSTF2"),
get_centered_overlaps(gr_cstf2t, gr_subset, "CSTF2Ï„")) %>%
plot_gr_density(palette="Reds", title=plot_title)
Cell Types Low
gr_subset <- gr_ctlow_novel
plot_title <- "Cell Types Low - novel"
c(get_centered_overlaps(gr_nudt21, gr_subset, "NUDT21"),
get_centered_overlaps(gr_cpsf6, gr_subset, "CPSF6")) %>%
plot_gr_density(palette="Blues", title=plot_title)
c(get_centered_overlaps(gr_cpsf1, gr_subset, "CPSF1"),
get_centered_overlaps(gr_cpsf2, gr_subset, "CPSF2"),
get_centered_overlaps(gr_cpsf3, gr_subset, "CPSF3"),
get_centered_overlaps(gr_cpsf4, gr_subset, "CPSF4"),
get_centered_overlaps(gr_wdr33, gr_subset, "WDR33"),
get_centered_overlaps(gr_fip1l1, gr_subset, "FIP1L1")) %>%
plot_gr_density(palette="Greens", title=plot_title)
c(get_centered_overlaps(gr_cstf2, gr_subset, "CSTF2"),
get_centered_overlaps(gr_cstf2t, gr_subset, "CSTF2Ï„")) %>%
plot_gr_density(palette="Reds", title=plot_title)
Internal Priming
gr_subset <- gr_ip
plot_title <- "Internal Priming"
c(get_centered_overlaps(gr_nudt21, gr_subset, "NUDT21"),
get_centered_overlaps(gr_cpsf6, gr_subset, "CPSF6")) %>%
plot_gr_density(palette="Blues", title=plot_title)
c(get_centered_overlaps(gr_cpsf1, gr_subset, "CPSF1"),
get_centered_overlaps(gr_cpsf2, gr_subset, "CPSF2"),
get_centered_overlaps(gr_cpsf3, gr_subset, "CPSF3"),
get_centered_overlaps(gr_cpsf4, gr_subset, "CPSF4"),
get_centered_overlaps(gr_wdr33, gr_subset, "WDR33"),
get_centered_overlaps(gr_fip1l1, gr_subset, "FIP1L1")) %>%
plot_gr_density(palette="Greens", title=plot_title)
c(get_centered_overlaps(gr_cstf2, gr_subset, "CSTF2"),
get_centered_overlaps(gr_cstf2t, gr_subset, "CSTF2Ï„")) %>%
plot_gr_density(palette="Reds", title=plot_title)
Runtime Details
Session Info
## R version 4.1.1 (2021-08-10)
## Platform: x86_64-apple-darwin13.4.0 (64-bit)
## Running under: macOS Big Sur 10.16
##
## Matrix products: default
## BLAS/LAPACK: /Users/mfansler/miniconda3/envs/bioc_3_14/lib/libopenblasp-r0.3.18.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats4 stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] cowplot_1.1.1 magrittr_2.0.3 forcats_0.5.1
## [4] stringr_1.4.0 dplyr_1.0.8 purrr_0.3.4
## [7] readr_2.1.1 tidyr_1.1.4 tibble_3.1.7
## [10] ggplot2_3.3.5 tidyverse_1.3.1 BiocParallel_1.28.0
## [13] plyranges_1.14.0 GenomicRanges_1.46.0 GenomeInfoDb_1.30.0
## [16] IRanges_2.28.0 S4Vectors_0.32.0 BiocGenerics_0.40.0
##
## loaded via a namespace (and not attached):
## [1] bitops_1.0-7 matrixStats_0.61.0
## [3] fs_1.5.2 bit64_4.0.5
## [5] lubridate_1.8.0 RColorBrewer_1.1-2
## [7] httr_1.4.2 tools_4.1.1
## [9] backports_1.4.0 bslib_0.3.1
## [11] utf8_1.2.2 R6_2.5.1
## [13] DBI_1.1.1 colorspace_2.0-2
## [15] withr_2.4.3 tidyselect_1.1.1
## [17] bit_4.0.4 compiler_4.1.1
## [19] rvest_1.0.2 cli_3.3.0
## [21] Biobase_2.54.0 xml2_1.3.3
## [23] DelayedArray_0.20.0 labeling_0.4.2
## [25] rtracklayer_1.54.0 sass_0.4.0
## [27] scales_1.1.1 digest_0.6.29
## [29] Rsamtools_2.10.0 rmarkdown_2.11
## [31] XVector_0.34.0 pkgconfig_2.0.3
## [33] htmltools_0.5.2 MatrixGenerics_1.6.0
## [35] highr_0.9 dbplyr_2.1.1
## [37] fastmap_1.1.0 rlang_1.0.2
## [39] readxl_1.3.1 rstudioapi_0.13
## [41] farver_2.1.0 jquerylib_0.1.4
## [43] BiocIO_1.4.0 generics_0.1.1
## [45] jsonlite_1.7.2 vroom_1.5.7
## [47] RCurl_1.98-1.5 GenomeInfoDbData_1.2.7
## [49] Matrix_1.3-4 Rcpp_1.0.7
## [51] munsell_0.5.0 fansi_0.5.0
## [53] lifecycle_1.0.1 stringi_1.7.6
## [55] yaml_2.2.1 SummarizedExperiment_1.24.0
## [57] zlibbioc_1.40.0 grid_4.1.1
## [59] parallel_4.1.1 crayon_1.4.2
## [61] lattice_0.20-45 Biostrings_2.62.0
## [63] haven_2.4.3 hms_1.1.1
## [65] knitr_1.39 pillar_1.7.0
## [67] rjson_0.2.20 reprex_2.0.1
## [69] XML_3.99-0.8 glue_1.6.2
## [71] evaluate_0.15 modelr_0.1.8
## [73] vctrs_0.4.1 tzdb_0.2.0
## [75] cellranger_1.1.0 gtable_0.3.0
## [77] assertthat_0.2.1 xfun_0.30
## [79] broom_0.8.0 restfulr_0.0.13
## [81] GenomicAlignments_1.30.0 ellipsis_0.3.2Conda Environment
## Conda Environment YAML
name: base
channels:
- conda-forge
- bioconda
- defaults
dependencies:
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- pip:
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prefix: /Users/mfansler/miniconda3